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Okta CEO: The next frontier of security is AI agent identity | The Verge
Ai Agents

Okta CEO: The next frontier of security is AI agent identity | The Verge

Todd McKinnon on why AI agents need an identity, security in an OpenClaw era, and being “paranoid” in preparing for the SaaSpocalypse.

The Verge - AI · 61 min ·
[2506.20964] Evidence-based diagnostic reasoning with multi-agent copilot for human pathology
Llms

[2506.20964] Evidence-based diagnostic reasoning with multi-agent copilot for human pathology

Abstract page for arXiv paper 2506.20964: Evidence-based diagnostic reasoning with multi-agent copilot for human pathology

arXiv - AI · 4 min ·
[2601.08323] AtomMem : Learnable Dynamic Agentic Memory with Atomic Memory Operation
Ai Agents

[2601.08323] AtomMem : Learnable Dynamic Agentic Memory with Atomic Memory Operation

Abstract page for arXiv paper 2601.08323: AtomMem : Learnable Dynamic Agentic Memory with Atomic Memory Operation

arXiv - AI · 3 min ·

All Content

[2603.00873] MC-Search: Evaluating and Enhancing Multimodal Agentic Search with Structured Long Reasoning Chains
Llms

[2603.00873] MC-Search: Evaluating and Enhancing Multimodal Agentic Search with Structured Long Reasoning Chains

Abstract page for arXiv paper 2603.00873: MC-Search: Evaluating and Enhancing Multimodal Agentic Search with Structured Long Reasoning Ch...

arXiv - AI · 4 min ·
[2603.00730] MO-MIX: Multi-Objective Multi-Agent Cooperative Decision-Making With Deep Reinforcement Learning
Ai Agents

[2603.00730] MO-MIX: Multi-Objective Multi-Agent Cooperative Decision-Making With Deep Reinforcement Learning

Abstract page for arXiv paper 2603.00730: MO-MIX: Multi-Objective Multi-Agent Cooperative Decision-Making With Deep Reinforcement Learning

arXiv - Machine Learning · 4 min ·
[2603.00623] TraceSIR: A Multi-Agent Framework for Structured Analysis and Reporting of Agentic Execution Traces
Llms

[2603.00623] TraceSIR: A Multi-Agent Framework for Structured Analysis and Reporting of Agentic Execution Traces

Abstract page for arXiv paper 2603.00623: TraceSIR: A Multi-Agent Framework for Structured Analysis and Reporting of Agentic Execution Tr...

arXiv - AI · 4 min ·
[2603.00540] LOGIGEN: Logic-Driven Generation of Verifiable Agentic Tasks
Llms

[2603.00540] LOGIGEN: Logic-Driven Generation of Verifiable Agentic Tasks

Abstract page for arXiv paper 2603.00540: LOGIGEN: Logic-Driven Generation of Verifiable Agentic Tasks

arXiv - AI · 4 min ·
[2603.00532] DenoiseFlow: Uncertainty-Aware Denoising for Reliable LLM Agentic Workflows
Llms

[2603.00532] DenoiseFlow: Uncertainty-Aware Denoising for Reliable LLM Agentic Workflows

Abstract page for arXiv paper 2603.00532: DenoiseFlow: Uncertainty-Aware Denoising for Reliable LLM Agentic Workflows

arXiv - AI · 4 min ·
[2603.00472] From Goals to Aspects, Revisited: An NFR Pattern Language for Agentic AI Systems
Machine Learning

[2603.00472] From Goals to Aspects, Revisited: An NFR Pattern Language for Agentic AI Systems

Abstract page for arXiv paper 2603.00472: From Goals to Aspects, Revisited: An NFR Pattern Language for Agentic AI Systems

arXiv - AI · 4 min ·
[2603.00267] Multi-Sourced, Multi-Agent Evidence Retrieval for Fact-Checking
Machine Learning

[2603.00267] Multi-Sourced, Multi-Agent Evidence Retrieval for Fact-Checking

Abstract page for arXiv paper 2603.00267: Multi-Sourced, Multi-Agent Evidence Retrieval for Fact-Checking

arXiv - AI · 4 min ·
[2603.00309] DIG to Heal: Scaling General-purpose Agent Collaboration via Explainable Dynamic Decision Paths
Llms

[2603.00309] DIG to Heal: Scaling General-purpose Agent Collaboration via Explainable Dynamic Decision Paths

Abstract page for arXiv paper 2603.00309: DIG to Heal: Scaling General-purpose Agent Collaboration via Explainable Dynamic Decision Paths

arXiv - AI · 4 min ·
[2603.00285] TraderBench: How Robust Are AI Agents in Adversarial Capital Markets?
Llms

[2603.00285] TraderBench: How Robust Are AI Agents in Adversarial Capital Markets?

Abstract page for arXiv paper 2603.00285: TraderBench: How Robust Are AI Agents in Adversarial Capital Markets?

arXiv - AI · 3 min ·
What Jobs Will AI Replace?
Ai Agents

What Jobs Will AI Replace?

The article discusses how AI is replacing certain jobs, particularly in customer service and programming, while also creating new roles t...

AI Events · 18 min ·
This AI Agent Is Ready to Serve, Mid-Phone Call | WIRED
Ai Agents

This AI Agent Is Ready to Serve, Mid-Phone Call | WIRED

Deutsche Telekom, the German cell provider—which holds a majority stake in T-Mobile—is partnering with ElevenLabs to enable an AI assista...

Wired - AI · 7 min ·
Llms

[P] Vera: a programming language designed for LLMs to write

I've built a programming language whose intended users are language models, not people. The compiler works end-to-end and it's MIT-licens...

Reddit - Machine Learning · 1 min ·
Machine Learning

Learning how to steer agentic AI in the right direction is a useless skill #changemymind

So, you wanna build an app. You have a design/architecture document that you want your agents to follow. That's great, that should be ALL...

Reddit - Artificial Intelligence · 1 min ·
[2602.01776] Position: Beyond Model-Centric Prediction -- Agentic Time Series Forecasting
Machine Learning

[2602.01776] Position: Beyond Model-Centric Prediction -- Agentic Time Series Forecasting

Abstract page for arXiv paper 2602.01776: Position: Beyond Model-Centric Prediction -- Agentic Time Series Forecasting

arXiv - Machine Learning · 4 min ·
[2511.21934] Heterogeneous Multi-Agent Reinforcement Learning with Attention for Cooperative and Scalable Feature Transformation
Machine Learning

[2511.21934] Heterogeneous Multi-Agent Reinforcement Learning with Attention for Cooperative and Scalable Feature Transformation

Abstract page for arXiv paper 2511.21934: Heterogeneous Multi-Agent Reinforcement Learning with Attention for Cooperative and Scalable Fe...

arXiv - Machine Learning · 4 min ·
[2511.18172] MEDIC: a network for monitoring data quality in collider experiments
Machine Learning

[2511.18172] MEDIC: a network for monitoring data quality in collider experiments

Abstract page for arXiv paper 2511.18172: MEDIC: a network for monitoring data quality in collider experiments

arXiv - Machine Learning · 4 min ·
[2511.17649] SWITCH: Benchmarking Modeling and Handling of Tangible Interfaces in Long-horizon Embodied Scenarios
Machine Learning

[2511.17649] SWITCH: Benchmarking Modeling and Handling of Tangible Interfaces in Long-horizon Embodied Scenarios

Abstract page for arXiv paper 2511.17649: SWITCH: Benchmarking Modeling and Handling of Tangible Interfaces in Long-horizon Embodied Scen...

arXiv - AI · 4 min ·
[2511.05271] DeepEyesV2: Toward Agentic Multimodal Model
Machine Learning

[2511.05271] DeepEyesV2: Toward Agentic Multimodal Model

Abstract page for arXiv paper 2511.05271: DeepEyesV2: Toward Agentic Multimodal Model

arXiv - AI · 4 min ·
[2508.12412] LumiMAS: A Comprehensive Framework for Real-Time Monitoring and Enhanced Observability in Multi-Agent Systems
Llms

[2508.12412] LumiMAS: A Comprehensive Framework for Real-Time Monitoring and Enhanced Observability in Multi-Agent Systems

Abstract page for arXiv paper 2508.12412: LumiMAS: A Comprehensive Framework for Real-Time Monitoring and Enhanced Observability in Multi...

arXiv - AI · 4 min ·
[2508.06269] OM2P: Offline Multi-Agent Mean-Flow Policy
Machine Learning

[2508.06269] OM2P: Offline Multi-Agent Mean-Flow Policy

Abstract page for arXiv paper 2508.06269: OM2P: Offline Multi-Agent Mean-Flow Policy

arXiv - Machine Learning · 4 min ·
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